{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "235 40\n"
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "tensor([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], requires_grad=True)"
     },
     "metadata": {},
     "execution_count": 1
    }
   ],
   "source": [
    "import torch\n",
    "import torchvision\n",
    "import torchvision.transforms as transforms\n",
    "import numpy as np \n",
    "\n",
    "mnist_train = torchvision.datasets.FashionMNIST(\"~/Datasets/FashionMNIST\",train=True,download=True,transform=transforms.ToTensor())\n",
    "mnist_test = torchvision.datasets.FashionMNIST(\"~/Datasets/FashionMNIST\",train=False,download=True,transform=transforms.ToTensor())\n",
    "\n",
    "batch_size = 256\n",
    "train_iter = torch.utils.data.DataLoader(mnist_train,batch_size=batch_size,shuffle=True,num_workers=4)\n",
    "test_iter = torch.utils.data.DataLoader(mnist_test,batch_size=batch_size,shuffle=True,num_workers=4)\n",
    "\n",
    "print(len(train_iter),len(test_iter))\n",
    "\n",
    "num_inputs = 28 * 28 # 输入节点个数，每个像素对应一个节点\n",
    "num_outputs = 10 # 输出节点个数，每个类别对应一个节点\n",
    "\n",
    "# 初始化参数，权重w和bias b\n",
    "# 权重矩阵的行数对应于输入节点的个数，列数对应于输出个数。 也就是，每一列都生成一个输出。\n",
    "W = torch.tensor(np.random.normal(0,0.01,(num_inputs,num_outputs)),dtype=torch.float32)\n",
    "b = torch.zeros(num_outputs,dtype=torch.float)\n",
    "\n",
    "W.requires_grad_(requires_grad=True)\n",
    "b.requires_grad_(requires_grad=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_data_fashion_mnist(batch_size):\n",
    "\n",
    "    mnist_train = torchvision.datasets.FashionMNIST(\"~/Datasets/FashionMNIST\",train=True,download=True,transform=transforms.ToTensor())\n",
    "    mnist_test = torchvision.datasets.FashionMNIST(\"~/Datasets/FashionMNIST\",train=False,download=True,transform=transforms.ToTensor())\n",
    "\n",
    "    \n",
    "    train_iter = torch.utils.data.DataLoader(mnist_train,batch_size=batch_size,shuffle=True,num_workers=4)\n",
    "    test_iter = torch.utils.data.DataLoader(mnist_test,batch_size=batch_size,shuffle=True,num_workers=4)\n",
    "\n",
    "    return train_iter,test_iter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 实现softmax\n",
    "\n",
    "如果对多维度的`tensor`对其**按维度操作**。 下面的代码中，矩阵$X$，对其中的同一列(dim=0)或者同一行(dim=1)进行操作"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "tensor([[5, 7, 9]])\ntensor([[ 6],\n        [15]])\n"
    }
   ],
   "source": [
    "x = torch.tensor([[1,2,3,],[4,5,6]])\n",
    "print(x.sum(dim=0,keepdim=True)) # 维度 hxw,dim=0，对行进行操作，求每一列的和\n",
    "print(x.sum(dim=1,keepdim=True)) # 维度 hxw,dim=1，对列进行操作，求每一行的和"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def softmax(X):\n",
    "    X_exp = X.exp()\n",
    "    partition = X_exp.sum(dim=1,keepdim=True)\n",
    "    return X_exp / partition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 定义模型\n",
    "def net(X):\n",
    "    X = X.float()\n",
    "    return softmax(torch.mm(X.view(-1,num_inputs),W) + b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "tensor([[0.1000],\n        [0.5000]])"
     },
     "metadata": {},
     "execution_count": 6
    }
   ],
   "source": [
    "y_hat = torch.tensor([[0.1,0.3,0.6],[0.3,0.2,0.5]]) # 2个样本，对应与3个类别的概率\n",
    "y = torch.LongTensor([0,2]) # 样本对应的真实类别\n",
    "y_hat.gather(1,y.view(-1,1)) # 取到真实的类别的预测概率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 定义损失函数\n",
    "def cross_entropy(y_hat,y):\n",
    "    return -torch.log(y_hat.gather(1,y.view(-1,1)))\n",
    "\n",
    "# 计算精度Accuracy\n",
    "def accuracy(y_hat,y):\n",
    "    return (y_hat.argmax(dim=1) == y).float().mean().item()\n",
    "\n",
    "def evaluate_accuracy(data_iter,net):\n",
    "    acc_sum,n = 0.0,0\n",
    "    for X,y in data_iter:\n",
    "        acc_sum += (net(X).argmax(dim=1) ==y).float().sum().item()\n",
    "        n += y.shape[0]\n",
    "\n",
    "    return acc_sum / n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": [
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend",
     "outputPrepend"
    ]
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "epoch 1,loss 0.7867,train acc 0.748,test_acc 0.796\nepoch 2,loss 0.5713,train acc 0.813,test_acc 0.811\nepoch 3,loss 0.5257,train acc 0.826,test_acc 0.820\nepoch 4,loss 0.5017,train acc 0.832,test_acc 0.825\nepoch 5,loss 0.4855,train acc 0.838,test_acc 0.828\n"
    }
   ],
   "source": [
    "# 训练模型\n",
    "import d2lzh as d2l\n",
    "num_epochs = 5\n",
    "lr = 0.1\n",
    "\n",
    "def train_ch3(net,train_iter,test_iter,loss,num_epochs,batch_size,params=None,lr=None,optimizer=None):\n",
    "    for epoch in range(num_epochs):\n",
    "        train_l_sum,train_acc_sum,n = 0.0,0.0,0\n",
    "        for X,y in train_iter:\n",
    "            y_hat = net(X)\n",
    "            l = loss(y_hat,y).sum()\n",
    "\n",
    "            # 梯度清零\n",
    "            if optimizer is not None:\n",
    "                optimizer.zero_grad()\n",
    "            elif params is not None and params[0].grad is not None:\n",
    "                for param in params:\n",
    "                    param.grad.data.zero_()\n",
    "\n",
    "            l.backward()\n",
    "            if optimizer is None:\n",
    "                # d2l.sgd(net,lr,batch_size)\n",
    "                for param in params:\n",
    "                    param.data -= lr * param.grad / batch_size\n",
    "            else:\n",
    "                optimizer.step()\n",
    "\n",
    "            train_l_sum += l.item()\n",
    "            train_acc_sum += (y_hat.argmax(dim=1) == y).sum().item()\n",
    "            n += y.shape[0]\n",
    "            test_acc = evaluate_accuracy(test_iter,net)\n",
    "\n",
    "        print(\"epoch %d,loss %.4f,train acc %.3f,test_acc %.3f\" % (epoch +1,train_l_sum / n ,train_acc_sum / n,test_acc))\n",
    "\n",
    "\n",
    "train_ch3(net,train_iter,test_iter,cross_entropy,num_epochs,batch_size,[W,b],lr,None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "[7 1 4 2 0 8 0 0 2 5 4 5 4 9 8 5 4 3 0 6 4 0 6 7 7 5 0 4 4 4 0 3 9 0 2 4 9\n 5 6 3 9 4 4 0 1 5 7 0 8 5 5 0 1 4 2 9 1 8 3 0 8 0 2 0 2 3 2 5 8 6 5 6 3 9\n 0 8 5 1 7 5 1 2 7 8 1 9 2 5 6 1 0 4 1 9 5 5 5 9 5 8 2 9 4 9 3 1 4 2 7 4 0\n 7 6 8 4 4 1 0 3 8 5 6 1 8 7 5 4 5 4 0 9 8 8 3 7 9 9 1 3 6 6 0 7 2 2 9 5 5\n 1 3 8 2 9 3 5 2 0 0 9 8 1 8 8 5 9 5 2 5 6 4 1 4 6 2 7 3 3 7 5 7 2 6 9 4 6\n 5 4 9 6 2 8 4 3 8 2 2 0 4 4 8 4 4 3 9 8 6 1 5 8 1 8 1 2 2 2 6 3 0 3 4 9 3\n 1 4 0 5 3 6 2 4 3 0 0 6 1 6 0 7 1 0 3 0 0 8 3 0 5 2 9 4 4 9 5 5 4 1]\n"
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 864x864 with 10 Axes>",
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Created with matplotlib (https://matplotlib.org/) -->\n<svg height=\"103.201263pt\" version=\"1.1\" viewBox=\"0 0 687.5 103.201263\" width=\"687.5pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n <defs>\n  <style type=\"text/css\">\n*{stroke-linecap:butt;stroke-linejoin:round;}\n  </style>\n </defs>\n <g id=\"figure_1\">\n  <g id=\"patch_1\">\n   <path d=\"M 0 103.201263 \nL 687.5 103.201263 \nL 687.5 -0 \nL 0 -0 \nz\n\" style=\"fill:none;\"/>\n  </g>\n  <g id=\"axes_1\">\n   <g id=\"patch_2\">\n    <path d=\"M 10.7 92.501263 \nL 67.445763 92.501263 \nL 67.445763 35.7555 \nL 10.7 35.7555 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#pf3eb4046c0)\">\n    <image height=\"57\" id=\"imagea908f293c0\" transform=\"scale(1 -1)translate(0 -57)\" width=\"57\" x=\"10.7\" xlink:href=\"data:image/png;base64,\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\" y=\"-35.501263\"/>\n   </g>\n   <g id=\"patch_3\">\n    <path d=\"M 10.7 92.501263 \nL 10.7 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_4\">\n    <path d=\"M 67.445763 92.501263 \nL 67.445763 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_5\">\n    <path d=\"M 10.7 92.501263 \nL 67.445763 92.501263 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_6\">\n    <path d=\"M 10.7 35.7555 \nL 67.445763 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_1\">\n    <!-- sneaker -->\n    <defs>\n     <path d=\"M 44.28125 53.078125 \nL 44.28125 44.578125 \nQ 40.484375 46.53125 36.375 47.5 \nQ 32.28125 48.484375 27.875 48.484375 \nQ 21.1875 48.484375 17.84375 46.4375 \nQ 14.5 44.390625 14.5 40.28125 \nQ 14.5 37.15625 16.890625 35.375 \nQ 19.28125 33.59375 26.515625 31.984375 \nL 29.59375 31.296875 \nQ 39.15625 29.25 43.1875 25.515625 \nQ 47.21875 21.78125 47.21875 15.09375 \nQ 47.21875 7.46875 41.1875 3.015625 \nQ 35.15625 -1.421875 24.609375 -1.421875 \nQ 20.21875 -1.421875 15.453125 -0.5625 \nQ 10.6875 0.296875 5.421875 2 \nL 5.421875 11.28125 \nQ 10.40625 8.6875 15.234375 7.390625 \nQ 20.0625 6.109375 24.8125 6.109375 \nQ 31.15625 6.109375 34.5625 8.28125 \nQ 37.984375 10.453125 37.984375 14.40625 \nQ 37.984375 18.0625 35.515625 20.015625 \nQ 33.0625 21.96875 24.703125 23.78125 \nL 21.578125 24.515625 \nQ 13.234375 26.265625 9.515625 29.90625 \nQ 5.8125 33.546875 5.8125 39.890625 \nQ 5.8125 47.609375 11.28125 51.796875 \nQ 16.75 56 26.8125 56 \nQ 31.78125 56 36.171875 55.265625 \nQ 40.578125 54.546875 44.28125 53.078125 \nz\n\" id=\"DejaVuSans-115\"/>\n     <path d=\"M 54.890625 33.015625 \nL 54.890625 0 \nL 45.90625 0 \nL 45.90625 32.71875 \nQ 45.90625 40.484375 42.875 44.328125 \nQ 39.84375 48.1875 33.796875 48.1875 \nQ 26.515625 48.1875 22.3125 43.546875 \nQ 18.109375 38.921875 18.109375 30.90625 \nL 18.109375 0 \nL 9.078125 0 \nL 9.078125 54.6875 \nL 18.109375 54.6875 \nL 18.109375 46.1875 \nQ 21.34375 51.125 25.703125 53.5625 \nQ 30.078125 56 35.796875 56 \nQ 45.21875 56 50.046875 50.171875 \nQ 54.890625 44.34375 54.890625 33.015625 \nz\n\" id=\"DejaVuSans-110\"/>\n     <path d=\"M 56.203125 29.59375 \nL 56.203125 25.203125 \nL 14.890625 25.203125 \nQ 15.484375 15.921875 20.484375 11.0625 \nQ 25.484375 6.203125 34.421875 6.203125 \nQ 39.59375 6.203125 44.453125 7.46875 \nQ 49.3125 8.734375 54.109375 11.28125 \nL 54.109375 2.78125 \nQ 49.265625 0.734375 44.1875 -0.34375 \nQ 39.109375 -1.421875 33.890625 -1.421875 \nQ 20.796875 -1.421875 13.15625 6.1875 \nQ 5.515625 13.8125 5.515625 26.8125 \nQ 5.515625 40.234375 12.765625 48.109375 \nQ 20.015625 56 32.328125 56 \nQ 43.359375 56 49.78125 48.890625 \nQ 56.203125 41.796875 56.203125 29.59375 \nz\nM 47.21875 32.234375 \nQ 47.125 39.59375 43.09375 43.984375 \nQ 39.0625 48.390625 32.421875 48.390625 \nQ 24.90625 48.390625 20.390625 44.140625 \nQ 15.875 39.890625 15.1875 32.171875 \nz\n\" id=\"DejaVuSans-101\"/>\n     <path d=\"M 34.28125 27.484375 \nQ 23.390625 27.484375 19.1875 25 \nQ 14.984375 22.515625 14.984375 16.5 \nQ 14.984375 11.71875 18.140625 8.90625 \nQ 21.296875 6.109375 26.703125 6.109375 \nQ 34.1875 6.109375 38.703125 11.40625 \nQ 43.21875 16.703125 43.21875 25.484375 \nL 43.21875 27.484375 \nz\nM 52.203125 31.203125 \nL 52.203125 0 \nL 43.21875 0 \nL 43.21875 8.296875 \nQ 40.140625 3.328125 35.546875 0.953125 \nQ 30.953125 -1.421875 24.3125 -1.421875 \nQ 15.921875 -1.421875 10.953125 3.296875 \nQ 6 8.015625 6 15.921875 \nQ 6 25.140625 12.171875 29.828125 \nQ 18.359375 34.515625 30.609375 34.515625 \nL 43.21875 34.515625 \nL 43.21875 35.40625 \nQ 43.21875 41.609375 39.140625 45 \nQ 35.0625 48.390625 27.6875 48.390625 \nQ 23 48.390625 18.546875 47.265625 \nQ 14.109375 46.140625 10.015625 43.890625 \nL 10.015625 52.203125 \nQ 14.9375 54.109375 19.578125 55.046875 \nQ 24.21875 56 28.609375 56 \nQ 40.484375 56 46.34375 49.84375 \nQ 52.203125 43.703125 52.203125 31.203125 \nz\n\" id=\"DejaVuSans-97\"/>\n     <path d=\"M 9.078125 75.984375 \nL 18.109375 75.984375 \nL 18.109375 31.109375 \nL 44.921875 54.6875 \nL 56.390625 54.6875 \nL 27.390625 29.109375 \nL 57.625 0 \nL 45.90625 0 \nL 18.109375 26.703125 \nL 18.109375 0 \nL 9.078125 0 \nz\n\" id=\"DejaVuSans-107\"/>\n     <path d=\"M 41.109375 46.296875 \nQ 39.59375 47.171875 37.8125 47.578125 \nQ 36.03125 48 33.890625 48 \nQ 26.265625 48 22.1875 43.046875 \nQ 18.109375 38.09375 18.109375 28.8125 \nL 18.109375 0 \nL 9.078125 0 \nL 9.078125 54.6875 \nL 18.109375 54.6875 \nL 18.109375 46.1875 \nQ 20.953125 51.171875 25.484375 53.578125 \nQ 30.03125 56 36.53125 56 \nQ 37.453125 56 38.578125 55.875 \nQ 39.703125 55.765625 41.0625 55.515625 \nz\n\" id=\"DejaVuSans-114\"/>\n    </defs>\n    <g transform=\"translate(15.360694 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-115\"/>\n     <use x=\"52.099609\" xlink:href=\"#DejaVuSans-110\"/>\n     <use x=\"115.478516\" xlink:href=\"#DejaVuSans-101\"/>\n     <use x=\"177.001953\" xlink:href=\"#DejaVuSans-97\"/>\n     <use x=\"238.28125\" xlink:href=\"#DejaVuSans-107\"/>\n     <use x=\"292.566406\" xlink:href=\"#DejaVuSans-101\"/>\n     <use x=\"354.089844\" xlink:href=\"#DejaVuSans-114\"/>\n    </g>\n    <!-- sneaker -->\n    <g transform=\"translate(15.360694 29.7555)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-115\"/>\n     <use x=\"52.099609\" xlink:href=\"#DejaVuSans-110\"/>\n     <use x=\"115.478516\" xlink:href=\"#DejaVuSans-101\"/>\n     <use x=\"177.001953\" xlink:href=\"#DejaVuSans-97\"/>\n     <use x=\"238.28125\" xlink:href=\"#DejaVuSans-107\"/>\n     <use x=\"292.566406\" xlink:href=\"#DejaVuSans-101\"/>\n     <use x=\"354.089844\" xlink:href=\"#DejaVuSans-114\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_2\">\n   <g id=\"patch_7\">\n    <path d=\"M 78.794915 92.501263 \nL 135.540678 92.501263 \nL 135.540678 35.7555 \nL 78.794915 35.7555 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#pe72736d313)\">\n    <image height=\"57\" id=\"imagecf45a993f7\" transform=\"scale(1 -1)translate(0 -57)\" width=\"57\" x=\"78.794915\" xlink:href=\"data:image/png;base64,\niVBORw0KGgoAAAANSUhEUgAAADkAAAA5CAYAAACMGIOFAAAABHNCSVQICAgIfAhkiAAACjFJREFUaIHNm0uPJEcRx3+RWVlV3T09PbOzu/YurL3yYoyFLNtYAgkhcUFCCHFBHDkiLhz4Nhy48gV8QVwQ3DhgIxsjhB8Y1hjb48fuPLu7qrIyg0M9pmdnbYyrhDek0Wiys7IyOiL+8Y/IHPmO/EgZKiLYL9+ivryFe/M96v33P/tSz36V/W8t2HnTk/3mRdDh20sGr9BKnOeUuynyyFXsYt6PS+XB18SjY+LJST9udxbIzgJNLFjbjy+/MMPPoZ4aMjGgYfDeRlFSrOX9b2xz+IznyvWCx3buAhBVePntLxL2J9z4bSD79Qv9Mwffe5IPvl+y2F7x2O4djCiJRLb0gL1o+Ov0S2w9L2gcvr/RLFlPwM1Lvn3t7/xg5yUAohp+lXyTFyc3WF/aIduYX1wyPHfzX3x1/h7f2noNJ4GUwJv+Kq+sbvDK5BaIGWVvoyipUdl6J1ItZqxvpXwtLVhpoFDlh5df5Jn52/zyoe+zs/FMtQ3f3fsrX8ne5em0IqB4jbxTe/653MMWwihmZERLmgC2EoxEtkxOiGuCBm4kh8ykIqbn56uFveSUHVOyZSZ4DXgCViJ1NDCOfsBYMWmE0+uG8ok1N/K7HMU1d0PgRBMumZpHkyX15DxK2hJeK64xlZJHkxMCSlQlF8/DkxP+kn7Myz6DjGNJMdRT2J6vmZuCqIpHKNSSSmBhJqi95xmFIjoKdfjWLQOKIZKaGh0nHAEYbalqW3ny8vvcSO/gxBBU8GoJH5PnQg7PTm/zcHJEoZGAYhE8liM/wQzPHL2MpmRMlcvZKTOp+rHwCctrAlftCTOpCZyFYFCDjxaGc4BexnFXI2AgMzVGPh1ihFx5Mq3wGikUKlUCSqGOqDKqkqNZUgWcBOwGLNpPgEg1sDATcmlmRcB3mxIFGWtnYyrpIpfdKU6aYLKiWBQr0r9JkgTk/rsP2vzMTMkXJofEdDxTjodhBjLjSWlABDjnugoNR70PiwmtPhFwBBZ2TUwYjfGMqKQyM2XjakBQIW7kgZgpdncHM8k/cRkrkdx4MA+iJduYBIht2ghIn0LUKkxyxF3EOrvhwRZt1nkQY5LYJPeo0v4p51OIAXXJubLq/yXjKdkl/3tM0Od0Aaz5WODZtKaROKolRyPouMil5BQnEY9+IhHYlID2wANQqeU05BvfznAZTUmxyrYpsCiVau+2n0Z6toMQMXi1SBzPlONUISIkWc2jyQGpRLxywW0BCBfJQVSlUoNtUdkQyYxvgGokGS0mXVpzxSpOwCMXlez2fA9hDyiehtBDm0KkfjDR1Rhlbpoi0KshauN2nWiiaO4Q5849F9v5pVq8GnLxXHcHaDpe1TyakomJZOIwNJu+YElRNL1/CulQ2avBSeBKcgzJeO46Hrq2EmlJAIagpgcVySJ+kWGWM8zhjJh0zOiMOFiUXAIzqTFuPHgdiRyeLRO0sUy8p7S3aaDaToizDJlO0Q1LdVYPCI7I3ATMgwQ84lIkyzCmsVlnyUIdK836HKiARCVmCexuo/dUGV4thTaOtTAWYx+gmBSXIFmKNWdu5zWhUEcRHb6LTRUkQkwNcTGFDWAJGLwmLGPTmV2YCUkSmmJ8BBkWkyKYh65QX9lmkR8CDegU6gj36USpgXpiCanB5jUAhcJJzFtiXvf5UqTpzKvI4POQYZYUQ31lm+UjU3azFbCh5H3QFWnOOMrdhCxr+gAe4TDMqNRiN3oeItpqOhw2Bq9Q7WasLhsWrgC68qrJk5v81bmAnxrKuaHYEaatkp0FoeGtHSlIkxpz9TJ2sT10i8PcVYxQ7iasrwqX0iXQxaS9QNBTV1NtCfVUqCfwcF6cfdbWoR5LbD1glnrqK9vNBg8PB7nswJg0hFQIE2VqmlZkX/Tq+Zbk7nTNh3u7VAul3gk8Nr8DNK7kpCZok1c7N5+6imIvx5T1oC127xgkdQ71LDK1JUDbvLoI/9dnR6yvBeTmki89/h7PzW838+XsGa9JX73sZGvWVxLqnXxwXA5nPMJ9ybSTgCOwigkfhSU3p3d49eYhN3fu8tTiXW6mH1GqJ2hjSTQ59+WkpsZPoc4tQ49FRqN1m8gY1JCbCouyVMe/a/j61j+4duuIJ7J3edwd4AROouARnIQ+5XSNsK2kws+FMHkA0DVaQZ1e6Jx3qOk14TBOcFJz3R2wZ5fMjWCBlSq+Vc5KxGw0oyemop5CnRtkICkYpqSR5twxC+Tiz39ExElgqSl3whYzqbjlPuS6rdg1E6wIhzFhqfd3pl23olpEqtlw1jPYkiGHdOqZmrIf6/IenLmxkdi7Yk2gaq14L5HvJDOeOI2E7HNWUkTwW8q13WP2klMAnMQeQLqi2UmNJWJRAlBoTaldSdY0oTdpYNDIwq5xi5J6xmB0HU7Qg1AGe26TmyBkiKQSGrRtlY+q/YstTTzfm3a8WurKYs5HwWeSQUqqKqaC0yJjFbMLnwc1WIk4qUmJOJSuL2CFZmzjJCzSgZDhqJ7CYYpb6uALEoNTiKmhqhKq1jVD38QymNZFO+TtjueCNh29TjYt35EBr40VZTjhGa6kLWG5cr0lvRqKmJKbqqdsTgJGmtbjUs2FnqyR2NDADZcvY4ItBFsN7xAMi8moSADqs4qjo2iOQCrhnJW6WrHifKPLov1zHQI3lpRR7g4MBh5TK9TSI6mRhgTkxjM3RX/SlUtg2iqwihmFJr2iTQPLMzdr8nb+OqQka7ClovHzLJpp3NWeWlYh6zfc/I73UL32tEul7+ZtHhB1dWg377jOSI8Ut/y8LxBqZHInUL6XsF+dFbdduZVJoGwViQheG1f1mjS3PMTiCFip8Jqw0oyy9Yh3ljvsvl6S7p8QBqLrsBQSlfS4Jr+rHPpJu6Ce46Cb0o12n3dAc79zk6JOcAcFcroe3OMZbMns9X327i7418klAHKJbJuClNhX+ZuSEpmZsu/oRTXEFogMZ8BztJqw/cZt6nVxYY3/VQYqqehqjTl2lOFsKSOxQdCNg9mCTWQ1fT6tNuIyF49XwwdhSVUmaOUhft4xCYTDQ0xVUfovAuBaJnMYJyw17V0yF09ufH+fLrbHCCdqqdSyl5zysD3mwzDnhfVl/MFFBvVZZXjRrIrWNUfHU/5YenJJmJqairIJQmliLhdPLjWpCaQaeus1TeiUmVTMjedPxR7P7z9D/kHygN13DYHZSxN+bH/Cz5/+HT9d3CYSgfLcNIO9MF7oKaVGMjFMJedn7z7H+hfXefStYzSMc+gzWvtj8qGyfmvKy489wj9nr1K0540Nd9U2P26wn3bcq8VrSi41U1PwzsGCR95aYj86ph7hPwlgrOvZIbD3h30Wb2zz++Qpbj97if3jOetVhk0C1kZCMMRgUBVUwSaBNA1YE7EmkiaB1AZ4aRv5258JZfnfX/wpZRxLqsLJkkQEdzrjznLK8jiHU0dwsTlQrQVCc/tRouBdpM4iYiPGKjYJJEkkWUNcF6Ogaif/AWBA9Vsf/Ve5AAAAAElFTkSuQmCC\" y=\"-35.501263\"/>\n   </g>\n   <g id=\"patch_8\">\n    <path d=\"M 78.794915 92.501263 \nL 78.794915 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_9\">\n    <path d=\"M 135.540678 92.501263 \nL 135.540678 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_10\">\n    <path d=\"M 78.794915 92.501263 \nL 135.540678 92.501263 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_11\">\n    <path d=\"M 78.794915 35.7555 \nL 135.540678 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_2\">\n    <!-- trouser -->\n    <defs>\n     <path d=\"M 18.3125 70.21875 \nL 18.3125 54.6875 \nL 36.8125 54.6875 \nL 36.8125 47.703125 \nL 18.3125 47.703125 \nL 18.3125 18.015625 \nQ 18.3125 11.328125 20.140625 9.421875 \nQ 21.96875 7.515625 27.59375 7.515625 \nL 36.8125 7.515625 \nL 36.8125 0 \nL 27.59375 0 \nQ 17.1875 0 13.234375 3.875 \nQ 9.28125 7.765625 9.28125 18.015625 \nL 9.28125 47.703125 \nL 2.6875 47.703125 \nL 2.6875 54.6875 \nL 9.28125 54.6875 \nL 9.28125 70.21875 \nz\n\" id=\"DejaVuSans-116\"/>\n     <path d=\"M 30.609375 48.390625 \nQ 23.390625 48.390625 19.1875 42.75 \nQ 14.984375 37.109375 14.984375 27.296875 \nQ 14.984375 17.484375 19.15625 11.84375 \nQ 23.34375 6.203125 30.609375 6.203125 \nQ 37.796875 6.203125 41.984375 11.859375 \nQ 46.1875 17.53125 46.1875 27.296875 \nQ 46.1875 37.015625 41.984375 42.703125 \nQ 37.796875 48.390625 30.609375 48.390625 \nz\nM 30.609375 56 \nQ 42.328125 56 49.015625 48.375 \nQ 55.71875 40.765625 55.71875 27.296875 \nQ 55.71875 13.875 49.015625 6.21875 \nQ 42.328125 -1.421875 30.609375 -1.421875 \nQ 18.84375 -1.421875 12.171875 6.21875 \nQ 5.515625 13.875 5.515625 27.296875 \nQ 5.515625 40.765625 12.171875 48.375 \nQ 18.84375 56 30.609375 56 \nz\n\" id=\"DejaVuSans-111\"/>\n     <path d=\"M 8.5 21.578125 \nL 8.5 54.6875 \nL 17.484375 54.6875 \nL 17.484375 21.921875 \nQ 17.484375 14.15625 20.5 10.265625 \nQ 23.53125 6.390625 29.59375 6.390625 \nQ 36.859375 6.390625 41.078125 11.03125 \nQ 45.3125 15.671875 45.3125 23.6875 \nL 45.3125 54.6875 \nL 54.296875 54.6875 \nL 54.296875 0 \nL 45.3125 0 \nL 45.3125 8.40625 \nQ 42.046875 3.421875 37.71875 1 \nQ 33.40625 -1.421875 27.6875 -1.421875 \nQ 18.265625 -1.421875 13.375 4.4375 \nQ 8.5 10.296875 8.5 21.578125 \nz\nM 31.109375 56 \nz\n\" id=\"DejaVuSans-117\"/>\n    </defs>\n    <g transform=\"translate(85.726234 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-116\"/>\n     <use x=\"39.208984\" xlink:href=\"#DejaVuSans-114\"/>\n     <use x=\"78.072266\" xlink:href=\"#DejaVuSans-111\"/>\n     <use x=\"139.253906\" xlink:href=\"#DejaVuSans-117\"/>\n     <use x=\"202.632812\" xlink:href=\"#DejaVuSans-115\"/>\n     <use x=\"254.732422\" xlink:href=\"#DejaVuSans-101\"/>\n     <use x=\"316.255859\" xlink:href=\"#DejaVuSans-114\"/>\n    </g>\n    <!-- trouser -->\n    <g transform=\"translate(85.726234 29.7555)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-116\"/>\n     <use x=\"39.208984\" xlink:href=\"#DejaVuSans-114\"/>\n     <use x=\"78.072266\" xlink:href=\"#DejaVuSans-111\"/>\n     <use x=\"139.253906\" xlink:href=\"#DejaVuSans-117\"/>\n     <use x=\"202.632812\" xlink:href=\"#DejaVuSans-115\"/>\n     <use x=\"254.732422\" xlink:href=\"#DejaVuSans-101\"/>\n     <use x=\"316.255859\" xlink:href=\"#DejaVuSans-114\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_3\">\n   <g id=\"patch_12\">\n    <path d=\"M 146.889831 92.501263 \nL 203.635593 92.501263 \nL 203.635593 35.7555 \nL 146.889831 35.7555 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p3566d864cc)\">\n    <image height=\"57\" id=\"image050c95e767\" transform=\"scale(1 -1)translate(0 -57)\" width=\"57\" x=\"146.889831\" xlink:href=\"data:image/png;base64,\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\" y=\"-35.501263\"/>\n   </g>\n   <g id=\"patch_13\">\n    <path d=\"M 146.889831 92.501263 \nL 146.889831 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_14\">\n    <path d=\"M 203.635593 92.501263 \nL 203.635593 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_15\">\n    <path d=\"M 146.889831 92.501263 \nL 203.635593 92.501263 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_16\">\n    <path d=\"M 146.889831 35.7555 \nL 203.635593 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_3\">\n    <!-- shirt -->\n    <defs>\n     <path d=\"M 54.890625 33.015625 \nL 54.890625 0 \nL 45.90625 0 \nL 45.90625 32.71875 \nQ 45.90625 40.484375 42.875 44.328125 \nQ 39.84375 48.1875 33.796875 48.1875 \nQ 26.515625 48.1875 22.3125 43.546875 \nQ 18.109375 38.921875 18.109375 30.90625 \nL 18.109375 0 \nL 9.078125 0 \nL 9.078125 75.984375 \nL 18.109375 75.984375 \nL 18.109375 46.1875 \nQ 21.34375 51.125 25.703125 53.5625 \nQ 30.078125 56 35.796875 56 \nQ 45.21875 56 50.046875 50.171875 \nQ 54.890625 44.34375 54.890625 33.015625 \nz\n\" id=\"DejaVuSans-104\"/>\n     <path d=\"M 9.421875 54.6875 \nL 18.40625 54.6875 \nL 18.40625 0 \nL 9.421875 0 \nz\nM 9.421875 75.984375 \nL 18.40625 75.984375 \nL 18.40625 64.59375 \nL 9.421875 64.59375 \nz\n\" id=\"DejaVuSans-105\"/>\n    </defs>\n    <g transform=\"translate(161.848962 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-115\"/>\n     <use x=\"52.099609\" xlink:href=\"#DejaVuSans-104\"/>\n     <use x=\"115.478516\" xlink:href=\"#DejaVuSans-105\"/>\n     <use x=\"143.261719\" xlink:href=\"#DejaVuSans-114\"/>\n     <use x=\"184.375\" xlink:href=\"#DejaVuSans-116\"/>\n    </g>\n    <!-- coat -->\n    <defs>\n     <path d=\"M 48.78125 52.59375 \nL 48.78125 44.1875 \nQ 44.96875 46.296875 41.140625 47.34375 \nQ 37.3125 48.390625 33.40625 48.390625 \nQ 24.65625 48.390625 19.8125 42.84375 \nQ 14.984375 37.3125 14.984375 27.296875 \nQ 14.984375 17.28125 19.8125 11.734375 \nQ 24.65625 6.203125 33.40625 6.203125 \nQ 37.3125 6.203125 41.140625 7.25 \nQ 44.96875 8.296875 48.78125 10.40625 \nL 48.78125 2.09375 \nQ 45.015625 0.34375 40.984375 -0.53125 \nQ 36.96875 -1.421875 32.421875 -1.421875 \nQ 20.0625 -1.421875 12.78125 6.34375 \nQ 5.515625 14.109375 5.515625 27.296875 \nQ 5.515625 40.671875 12.859375 48.328125 \nQ 20.21875 56 33.015625 56 \nQ 37.15625 56 41.109375 55.140625 \nQ 45.0625 54.296875 48.78125 52.59375 \nz\n\" id=\"DejaVuSans-99\"/>\n    </defs>\n    <g transform=\"translate(162.263337 29.7555)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-99\"/>\n     <use x=\"54.980469\" xlink:href=\"#DejaVuSans-111\"/>\n     <use x=\"116.162109\" xlink:href=\"#DejaVuSans-97\"/>\n     <use x=\"177.441406\" xlink:href=\"#DejaVuSans-116\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_4\">\n   <g id=\"patch_17\">\n    <path d=\"M 214.984746 92.501263 \nL 271.730508 92.501263 \nL 271.730508 35.7555 \nL 214.984746 35.7555 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p104c0ab20a)\">\n    <image height=\"57\" id=\"image59c0cc7bdc\" transform=\"scale(1 -1)translate(0 -57)\" width=\"57\" x=\"214.984746\" xlink:href=\"data:image/png;base64,\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\" y=\"-35.501263\"/>\n   </g>\n   <g id=\"patch_18\">\n    <path d=\"M 214.984746 92.501263 \nL 214.984746 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_19\">\n    <path d=\"M 271.730508 92.501263 \nL 271.730508 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_20\">\n    <path d=\"M 214.984746 92.501263 \nL 271.730508 92.501263 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_21\">\n    <path d=\"M 214.984746 35.7555 \nL 271.730508 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_4\">\n    <!-- pullover -->\n    <defs>\n     <path d=\"M 18.109375 8.203125 \nL 18.109375 -20.796875 \nL 9.078125 -20.796875 \nL 9.078125 54.6875 \nL 18.109375 54.6875 \nL 18.109375 46.390625 \nQ 20.953125 51.265625 25.265625 53.625 \nQ 29.59375 56 35.59375 56 \nQ 45.5625 56 51.78125 48.09375 \nQ 58.015625 40.1875 58.015625 27.296875 \nQ 58.015625 14.40625 51.78125 6.484375 \nQ 45.5625 -1.421875 35.59375 -1.421875 \nQ 29.59375 -1.421875 25.265625 0.953125 \nQ 20.953125 3.328125 18.109375 8.203125 \nz\nM 48.6875 27.296875 \nQ 48.6875 37.203125 44.609375 42.84375 \nQ 40.53125 48.484375 33.40625 48.484375 \nQ 26.265625 48.484375 22.1875 42.84375 \nQ 18.109375 37.203125 18.109375 27.296875 \nQ 18.109375 17.390625 22.1875 11.75 \nQ 26.265625 6.109375 33.40625 6.109375 \nQ 40.53125 6.109375 44.609375 11.75 \nQ 48.6875 17.390625 48.6875 27.296875 \nz\n\" id=\"DejaVuSans-112\"/>\n     <path d=\"M 9.421875 75.984375 \nL 18.40625 75.984375 \nL 18.40625 0 \nL 9.421875 0 \nz\n\" id=\"DejaVuSans-108\"/>\n     <path d=\"M 2.984375 54.6875 \nL 12.5 54.6875 \nL 29.59375 8.796875 \nL 46.6875 54.6875 \nL 56.203125 54.6875 \nL 35.6875 0 \nL 23.484375 0 \nz\n\" id=\"DejaVuSans-118\"/>\n    </defs>\n    <g transform=\"translate(219.031377 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-112\"/>\n     <use x=\"63.476562\" xlink:href=\"#DejaVuSans-117\"/>\n     <use x=\"126.855469\" xlink:href=\"#DejaVuSans-108\"/>\n     <use x=\"154.638672\" xlink:href=\"#DejaVuSans-108\"/>\n     <use x=\"182.421875\" xlink:href=\"#DejaVuSans-111\"/>\n     <use x=\"243.603516\" xlink:href=\"#DejaVuSans-118\"/>\n     <use x=\"302.783203\" xlink:href=\"#DejaVuSans-101\"/>\n     <use x=\"364.306641\" xlink:href=\"#DejaVuSans-114\"/>\n    </g>\n    <!-- pullover -->\n    <g transform=\"translate(219.031377 29.7555)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-112\"/>\n     <use x=\"63.476562\" xlink:href=\"#DejaVuSans-117\"/>\n     <use x=\"126.855469\" xlink:href=\"#DejaVuSans-108\"/>\n     <use x=\"154.638672\" xlink:href=\"#DejaVuSans-108\"/>\n     <use x=\"182.421875\" xlink:href=\"#DejaVuSans-111\"/>\n     <use x=\"243.603516\" xlink:href=\"#DejaVuSans-118\"/>\n     <use x=\"302.783203\" xlink:href=\"#DejaVuSans-101\"/>\n     <use x=\"364.306641\" xlink:href=\"#DejaVuSans-114\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_5\">\n   <g id=\"patch_22\">\n    <path d=\"M 283.079661 92.501263 \nL 339.825424 92.501263 \nL 339.825424 35.7555 \nL 283.079661 35.7555 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p13356c8c21)\">\n    <image height=\"57\" id=\"image6a68eefe04\" transform=\"scale(1 -1)translate(0 -57)\" width=\"57\" x=\"283.079661\" xlink:href=\"data:image/png;base64,\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\" y=\"-35.501263\"/>\n   </g>\n   <g id=\"patch_23\">\n    <path d=\"M 283.079661 92.501263 \nL 283.079661 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_24\">\n    <path d=\"M 339.825424 92.501263 \nL 339.825424 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_25\">\n    <path d=\"M 283.079661 92.501263 \nL 339.825424 92.501263 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_26\">\n    <path d=\"M 283.079661 35.7555 \nL 339.825424 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_5\">\n    <!-- t-shirt -->\n    <defs>\n     <path d=\"M 4.890625 31.390625 \nL 31.203125 31.390625 \nL 31.203125 23.390625 \nL 4.890625 23.390625 \nz\n\" id=\"DejaVuSans-45\"/>\n    </defs>\n    <g transform=\"translate(293.521917 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-116\"/>\n     <use x=\"39.208984\" xlink:href=\"#DejaVuSans-45\"/>\n     <use x=\"75.292969\" xlink:href=\"#DejaVuSans-115\"/>\n     <use x=\"127.392578\" xlink:href=\"#DejaVuSans-104\"/>\n     <use x=\"190.771484\" xlink:href=\"#DejaVuSans-105\"/>\n     <use x=\"218.554688\" xlink:href=\"#DejaVuSans-114\"/>\n     <use x=\"259.667969\" xlink:href=\"#DejaVuSans-116\"/>\n    </g>\n    <!-- t-shirt -->\n    <g transform=\"translate(293.521917 29.7555)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-116\"/>\n     <use x=\"39.208984\" xlink:href=\"#DejaVuSans-45\"/>\n     <use x=\"75.292969\" xlink:href=\"#DejaVuSans-115\"/>\n     <use x=\"127.392578\" xlink:href=\"#DejaVuSans-104\"/>\n     <use x=\"190.771484\" xlink:href=\"#DejaVuSans-105\"/>\n     <use x=\"218.554688\" xlink:href=\"#DejaVuSans-114\"/>\n     <use x=\"259.667969\" xlink:href=\"#DejaVuSans-116\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_6\">\n   <g id=\"patch_27\">\n    <path d=\"M 351.174576 92.501263 \nL 407.920339 92.501263 \nL 407.920339 35.7555 \nL 351.174576 35.7555 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p5507fdc2c4)\">\n    <image height=\"57\" id=\"image00729c260b\" transform=\"scale(1 -1)translate(0 -57)\" width=\"57\" x=\"351.174576\" xlink:href=\"data:image/png;base64,\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\" y=\"-35.501263\"/>\n   </g>\n   <g id=\"patch_28\">\n    <path d=\"M 351.174576 92.501263 \nL 351.174576 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_29\">\n    <path d=\"M 407.920339 92.501263 \nL 407.920339 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_30\">\n    <path d=\"M 351.174576 92.501263 \nL 407.920339 92.501263 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_31\">\n    <path d=\"M 351.174576 35.7555 \nL 407.920339 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_6\">\n    <!-- bag -->\n    <defs>\n     <path d=\"M 48.6875 27.296875 \nQ 48.6875 37.203125 44.609375 42.84375 \nQ 40.53125 48.484375 33.40625 48.484375 \nQ 26.265625 48.484375 22.1875 42.84375 \nQ 18.109375 37.203125 18.109375 27.296875 \nQ 18.109375 17.390625 22.1875 11.75 \nQ 26.265625 6.109375 33.40625 6.109375 \nQ 40.53125 6.109375 44.609375 11.75 \nQ 48.6875 17.390625 48.6875 27.296875 \nz\nM 18.109375 46.390625 \nQ 20.953125 51.265625 25.265625 53.625 \nQ 29.59375 56 35.59375 56 \nQ 45.5625 56 51.78125 48.09375 \nQ 58.015625 40.1875 58.015625 27.296875 \nQ 58.015625 14.40625 51.78125 6.484375 \nQ 45.5625 -1.421875 35.59375 -1.421875 \nQ 29.59375 -1.421875 25.265625 0.953125 \nQ 20.953125 3.328125 18.109375 8.203125 \nL 18.109375 0 \nL 9.078125 0 \nL 9.078125 75.984375 \nL 18.109375 75.984375 \nz\n\" id=\"DejaVuSans-98\"/>\n     <path d=\"M 45.40625 27.984375 \nQ 45.40625 37.75 41.375 43.109375 \nQ 37.359375 48.484375 30.078125 48.484375 \nQ 22.859375 48.484375 18.828125 43.109375 \nQ 14.796875 37.75 14.796875 27.984375 \nQ 14.796875 18.265625 18.828125 12.890625 \nQ 22.859375 7.515625 30.078125 7.515625 \nQ 37.359375 7.515625 41.375 12.890625 \nQ 45.40625 18.265625 45.40625 27.984375 \nz\nM 54.390625 6.78125 \nQ 54.390625 -7.171875 48.1875 -13.984375 \nQ 42 -20.796875 29.203125 -20.796875 \nQ 24.46875 -20.796875 20.265625 -20.09375 \nQ 16.0625 -19.390625 12.109375 -17.921875 \nL 12.109375 -9.1875 \nQ 16.0625 -11.328125 19.921875 -12.34375 \nQ 23.78125 -13.375 27.78125 -13.375 \nQ 36.625 -13.375 41.015625 -8.765625 \nQ 45.40625 -4.15625 45.40625 5.171875 \nL 45.40625 9.625 \nQ 42.625 4.78125 38.28125 2.390625 \nQ 33.9375 0 27.875 0 \nQ 17.828125 0 11.671875 7.65625 \nQ 5.515625 15.328125 5.515625 27.984375 \nQ 5.515625 40.671875 11.671875 48.328125 \nQ 17.828125 56 27.875 56 \nQ 33.9375 56 38.28125 53.609375 \nQ 42.625 51.21875 45.40625 46.390625 \nL 45.40625 54.6875 \nL 54.390625 54.6875 \nz\n\" id=\"DejaVuSans-103\"/>\n    </defs>\n    <g transform=\"translate(368.252458 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-98\"/>\n     <use x=\"63.476562\" xlink:href=\"#DejaVuSans-97\"/>\n     <use x=\"124.755859\" xlink:href=\"#DejaVuSans-103\"/>\n    </g>\n    <!-- bag -->\n    <g transform=\"translate(368.252458 29.7555)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-98\"/>\n     <use x=\"63.476562\" xlink:href=\"#DejaVuSans-97\"/>\n     <use x=\"124.755859\" xlink:href=\"#DejaVuSans-103\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_7\">\n   <g id=\"patch_32\">\n    <path d=\"M 419.269492 92.501263 \nL 476.015254 92.501263 \nL 476.015254 35.7555 \nL 419.269492 35.7555 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p33a13ac1b3)\">\n    <image height=\"57\" id=\"imagec8c61971a2\" transform=\"scale(1 -1)translate(0 -57)\" width=\"57\" x=\"419.269492\" xlink:href=\"data:image/png;base64,\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\" y=\"-35.501263\"/>\n   </g>\n   <g id=\"patch_33\">\n    <path d=\"M 419.269492 92.501263 \nL 419.269492 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_34\">\n    <path d=\"M 476.015254 92.501263 \nL 476.015254 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_35\">\n    <path d=\"M 419.269492 92.501263 \nL 476.015254 92.501263 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_36\">\n    <path d=\"M 419.269492 35.7555 \nL 476.015254 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_7\">\n    <!-- t-shirt -->\n    <g transform=\"translate(429.711748 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-116\"/>\n     <use x=\"39.208984\" xlink:href=\"#DejaVuSans-45\"/>\n     <use x=\"75.292969\" xlink:href=\"#DejaVuSans-115\"/>\n     <use x=\"127.392578\" xlink:href=\"#DejaVuSans-104\"/>\n     <use x=\"190.771484\" xlink:href=\"#DejaVuSans-105\"/>\n     <use x=\"218.554688\" xlink:href=\"#DejaVuSans-114\"/>\n     <use x=\"259.667969\" xlink:href=\"#DejaVuSans-116\"/>\n    </g>\n    <!-- t-shirt -->\n    <g transform=\"translate(429.711748 29.7555)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-116\"/>\n     <use x=\"39.208984\" xlink:href=\"#DejaVuSans-45\"/>\n     <use x=\"75.292969\" xlink:href=\"#DejaVuSans-115\"/>\n     <use x=\"127.392578\" xlink:href=\"#DejaVuSans-104\"/>\n     <use x=\"190.771484\" xlink:href=\"#DejaVuSans-105\"/>\n     <use x=\"218.554688\" xlink:href=\"#DejaVuSans-114\"/>\n     <use x=\"259.667969\" xlink:href=\"#DejaVuSans-116\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_8\">\n   <g id=\"patch_37\">\n    <path d=\"M 487.364407 92.501263 \nL 544.110169 92.501263 \nL 544.110169 35.7555 \nL 487.364407 35.7555 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p9fdff61d8f)\">\n    <image height=\"57\" id=\"image1c43ecb646\" transform=\"scale(1 -1)translate(0 -57)\" width=\"57\" x=\"487.364407\" xlink:href=\"data:image/png;base64,\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\" y=\"-35.501263\"/>\n   </g>\n   <g id=\"patch_38\">\n    <path d=\"M 487.364407 92.501263 \nL 487.364407 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_39\">\n    <path d=\"M 544.110169 92.501263 \nL 544.110169 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_40\">\n    <path d=\"M 487.364407 92.501263 \nL 544.110169 92.501263 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_41\">\n    <path d=\"M 487.364407 35.7555 \nL 544.110169 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_8\">\n    <!-- shirt -->\n    <g transform=\"translate(502.323538 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-115\"/>\n     <use x=\"52.099609\" xlink:href=\"#DejaVuSans-104\"/>\n     <use x=\"115.478516\" xlink:href=\"#DejaVuSans-105\"/>\n     <use x=\"143.261719\" xlink:href=\"#DejaVuSans-114\"/>\n     <use x=\"184.375\" xlink:href=\"#DejaVuSans-116\"/>\n    </g>\n    <!-- t-shirt -->\n    <g transform=\"translate(497.806663 29.7555)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-116\"/>\n     <use x=\"39.208984\" xlink:href=\"#DejaVuSans-45\"/>\n     <use x=\"75.292969\" xlink:href=\"#DejaVuSans-115\"/>\n     <use x=\"127.392578\" xlink:href=\"#DejaVuSans-104\"/>\n     <use x=\"190.771484\" xlink:href=\"#DejaVuSans-105\"/>\n     <use x=\"218.554688\" xlink:href=\"#DejaVuSans-114\"/>\n     <use x=\"259.667969\" xlink:href=\"#DejaVuSans-116\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_9\">\n   <g id=\"patch_42\">\n    <path d=\"M 555.459322 92.501263 \nL 612.205085 92.501263 \nL 612.205085 35.7555 \nL 555.459322 35.7555 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#pf1cc3afed9)\">\n    <image height=\"57\" id=\"image85d4d387e8\" transform=\"scale(1 -1)translate(0 -57)\" width=\"57\" x=\"555.459322\" xlink:href=\"data:image/png;base64,\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\" y=\"-35.501263\"/>\n   </g>\n   <g id=\"patch_43\">\n    <path d=\"M 555.459322 92.501263 \nL 555.459322 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_44\">\n    <path d=\"M 612.205085 92.501263 \nL 612.205085 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_45\">\n    <path d=\"M 555.459322 92.501263 \nL 612.205085 92.501263 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_46\">\n    <path d=\"M 555.459322 35.7555 \nL 612.205085 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_9\">\n    <!-- pullover -->\n    <g transform=\"translate(559.505953 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-112\"/>\n     <use x=\"63.476562\" xlink:href=\"#DejaVuSans-117\"/>\n     <use x=\"126.855469\" xlink:href=\"#DejaVuSans-108\"/>\n     <use x=\"154.638672\" xlink:href=\"#DejaVuSans-108\"/>\n     <use x=\"182.421875\" xlink:href=\"#DejaVuSans-111\"/>\n     <use x=\"243.603516\" xlink:href=\"#DejaVuSans-118\"/>\n     <use x=\"302.783203\" xlink:href=\"#DejaVuSans-101\"/>\n     <use x=\"364.306641\" xlink:href=\"#DejaVuSans-114\"/>\n    </g>\n    <!-- pullover -->\n    <g transform=\"translate(559.505953 29.7555)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-112\"/>\n     <use x=\"63.476562\" xlink:href=\"#DejaVuSans-117\"/>\n     <use x=\"126.855469\" xlink:href=\"#DejaVuSans-108\"/>\n     <use x=\"154.638672\" xlink:href=\"#DejaVuSans-108\"/>\n     <use x=\"182.421875\" xlink:href=\"#DejaVuSans-111\"/>\n     <use x=\"243.603516\" xlink:href=\"#DejaVuSans-118\"/>\n     <use x=\"302.783203\" xlink:href=\"#DejaVuSans-101\"/>\n     <use x=\"364.306641\" xlink:href=\"#DejaVuSans-114\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_10\">\n   <g id=\"patch_47\">\n    <path d=\"M 623.554237 92.501263 \nL 680.3 92.501263 \nL 680.3 35.7555 \nL 623.554237 35.7555 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p2048432b23)\">\n    <image height=\"57\" id=\"image55c1aaf9d8\" transform=\"scale(1 -1)translate(0 -57)\" width=\"57\" x=\"623.554237\" xlink:href=\"data:image/png;base64,\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\" y=\"-35.501263\"/>\n   </g>\n   <g id=\"patch_48\">\n    <path d=\"M 623.554237 92.501263 \nL 623.554237 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_49\">\n    <path d=\"M 680.3 92.501263 \nL 680.3 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_50\">\n    <path d=\"M 623.554237 92.501263 \nL 680.3 92.501263 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_51\">\n    <path d=\"M 623.554237 35.7555 \nL 680.3 35.7555 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_10\">\n    <!-- sandal -->\n    <defs>\n     <path d=\"M 45.40625 46.390625 \nL 45.40625 75.984375 \nL 54.390625 75.984375 \nL 54.390625 0 \nL 45.40625 0 \nL 45.40625 8.203125 \nQ 42.578125 3.328125 38.25 0.953125 \nQ 33.9375 -1.421875 27.875 -1.421875 \nQ 17.96875 -1.421875 11.734375 6.484375 \nQ 5.515625 14.40625 5.515625 27.296875 \nQ 5.515625 40.1875 11.734375 48.09375 \nQ 17.96875 56 27.875 56 \nQ 33.9375 56 38.25 53.625 \nQ 42.578125 51.265625 45.40625 46.390625 \nz\nM 14.796875 27.296875 \nQ 14.796875 17.390625 18.875 11.75 \nQ 22.953125 6.109375 30.078125 6.109375 \nQ 37.203125 6.109375 41.296875 11.75 \nQ 45.40625 17.390625 45.40625 27.296875 \nQ 45.40625 37.203125 41.296875 42.84375 \nQ 37.203125 48.484375 30.078125 48.484375 \nQ 22.953125 48.484375 18.875 42.84375 \nQ 14.796875 37.203125 14.796875 27.296875 \nz\n\" id=\"DejaVuSans-100\"/>\n    </defs>\n    <g transform=\"translate(632.169306 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-115\"/>\n     <use x=\"52.099609\" xlink:href=\"#DejaVuSans-97\"/>\n     <use x=\"113.378906\" xlink:href=\"#DejaVuSans-110\"/>\n     <use x=\"176.757812\" xlink:href=\"#DejaVuSans-100\"/>\n     <use x=\"240.234375\" xlink:href=\"#DejaVuSans-97\"/>\n     <use x=\"301.513672\" xlink:href=\"#DejaVuSans-108\"/>\n    </g>\n    <!-- sandal -->\n    <g transform=\"translate(632.169306 29.7555)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-115\"/>\n     <use x=\"52.099609\" xlink:href=\"#DejaVuSans-97\"/>\n     <use x=\"113.378906\" xlink:href=\"#DejaVuSans-110\"/>\n     <use x=\"176.757812\" xlink:href=\"#DejaVuSans-100\"/>\n     <use x=\"240.234375\" xlink:href=\"#DejaVuSans-97\"/>\n     <use x=\"301.513672\" xlink:href=\"#DejaVuSans-108\"/>\n    </g>\n   </g>\n  </g>\n </g>\n <defs>\n  <clipPath id=\"pf3eb4046c0\">\n   <rect height=\"56.745763\" width=\"56.745763\" x=\"10.7\" y=\"35.7555\"/>\n  </clipPath>\n  <clipPath id=\"pe72736d313\">\n   <rect height=\"56.745763\" width=\"56.745763\" x=\"78.794915\" y=\"35.7555\"/>\n  </clipPath>\n  <clipPath id=\"p3566d864cc\">\n   <rect height=\"56.745763\" width=\"56.745763\" x=\"146.889831\" y=\"35.7555\"/>\n  </clipPath>\n  <clipPath id=\"p104c0ab20a\">\n   <rect height=\"56.745763\" width=\"56.745763\" x=\"214.984746\" y=\"35.7555\"/>\n  </clipPath>\n  <clipPath id=\"p13356c8c21\">\n   <rect height=\"56.745763\" width=\"56.745763\" x=\"283.079661\" y=\"35.7555\"/>\n  </clipPath>\n  <clipPath id=\"p5507fdc2c4\">\n   <rect height=\"56.745763\" width=\"56.745763\" x=\"351.174576\" y=\"35.7555\"/>\n  </clipPath>\n  <clipPath id=\"p33a13ac1b3\">\n   <rect height=\"56.745763\" width=\"56.745763\" x=\"419.269492\" y=\"35.7555\"/>\n  </clipPath>\n  <clipPath id=\"p9fdff61d8f\">\n   <rect height=\"56.745763\" width=\"56.745763\" x=\"487.364407\" y=\"35.7555\"/>\n  </clipPath>\n  <clipPath id=\"pf1cc3afed9\">\n   <rect height=\"56.745763\" width=\"56.745763\" x=\"555.459322\" y=\"35.7555\"/>\n  </clipPath>\n  <clipPath id=\"p2048432b23\">\n   <rect height=\"56.745763\" width=\"56.745763\" x=\"623.554237\" y=\"35.7555\"/>\n  </clipPath>\n </defs>\n</svg>\n",
      "image/png": "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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "import d2lzh as d2l\n",
    "\n",
    "X,y = iter(test_iter).next()\n",
    "\n",
    "X,y = iter(train_iter).next()\n",
    "print(net(X).argmax(dim=1).numpy())\n",
    "true_labels = d2l.get_fashion_mnist_labels(y.numpy())\n",
    "pred_labels = d2l.get_fashion_mnist_labels(net(X).argmax(dim=1).numpy())\n",
    "\n",
    "\n",
    "\n",
    "titles = [true + \"\\n\" + pred for true,pred in zip(true_labels,pred_labels)]\n",
    "\n",
    "d2l.show_fashion_mnist(X[0:10],titles[0:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7-final"
  },
  "orig_nbformat": 2,
  "kernelspec": {
   "name": "python37764bitpytorchnotebookconda6e7a8693df0d4d92aca09d521275d23a",
   "display_name": "Python 3.7.7 64-bit ('pytorch_notebook': conda)"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}